We also considered a volume-weighted \(\rho (t)\) , which amounts to weighing probabilities for different vacua by their physical volume.
This prior peaks at late times, and as such is maximally informative. Interestingly, because volume weighing is implemented as a prior, the resulting
probabilities do not suffer from the usual sensitivity to the choice of time variable and the associated paradoxes. Instead, the predictive
distribution is time-reparametrization invariant, and agrees with the GSVW measure [1]}.
